One of the most frequent complications experienced by patients suffering from insulin dependant diabetes mellitus is the phenomenon of hypoglycaemia.
Hypoglycaemia is a physiological condition where the blood glucose level of the patient decreases below a certain value. Blood glucose levels below approx. 2.5 mmol/L may give rise to serious symptoms and may potentially even become dangerous for a diabetic patient, in particular, if the patient does not become aware of the condition, e.g. because the patient is sleeping or preoccupied with another activity, e.g. driving a car.
Already during the onset of hypoglycaemia more moderate drops of the blood glucose level, e.g. below approximately 3.8 mmol/L glucagon, cause epinephrine, growth hormone, and cortisol to be released, resulting in symptoms such as rise in pulse, lowering of the variability of the heart rate and increased perspiration.
Hence, there is a strong desire to allow for a monitoring of a patient to avoid an undetected occurrence of hypoglycaemia. Even though glucose meters which only require small blood samples exist, frequent measurements of the glucose level in blood samples taken from the patient are painful and not suited for a continuous monitoring.
U.S. Pat. No. 4,509,531 discloses a non-invasive watch-like monitoring device that measures body temperature and skin resistance. In the event of either a predetermined change in galvanic skin resistance or a predetermined change in peripheral skin temperature an alarm is generated which can waken a sleeper wearing the monitoring device.
Another watch-like device that uses perspiration and a drop in skin temperature to detect hypoglycaemia is the Sleep Sentry by Diabetes Sentry Products Inc. Studies for this device have shown that, when hypoglycaemia was confirmed to be present, the alarm was generated about 90% of the time, thereby leaving about 10% of the occurrences undetected. Furthermore, it is not uncommon for patients to experience a false alarm.
Hence, in the light of the above prior art devices it is desirable to increase the reliability of the hypoglycaemia detection.
International patent application WO 02/069798 discloses a method of determining the presence of a physiological condition in a person where the person's skin impedance, heart rate, QT interval and mean or peak frequency of the α wave are measured. The measured input data are fed into a multilayer feedforward neural network which is trained to calculate the patient's blood glucose status. The neural network is trained using the back-propagation algorithm in which synaptic strengths are systematically modified so that the response of the network approximates the blood glucose status of the patient with increasing accuracy.
It is a problem of the above prior art system that the actual performance of the neural network can only be assessed based on statistical methods. Hence, an explicit validation of the output for all possible sets of input data is unfeasible. However, since such a system is used in a medical context, it is desirable to provide a system with a reliability which may be systematically validated over the entire range of measured sensor values.
It is a further problem of the above prior art method that the back-propagation algorithm is time-consuming.